Various types of errors are encountered by banking machines, ATMs, cash handling devices, and the like, such as hardware issues in the system, legibility issues with the check images, unexpected system crashes, and the erroneous rejecting of cash or checks. Traditional error tracking and classification systems for cash handling machines lack capabilities for processing sufficient information that will allow efficient servicing. The disclosure herein relates to methods of tracking these errors and determining when a particular machine needs to be serviced or replaced based on the number of errors and the frequency of the errors by the machine, resulting in an improvement to resource usage for servicing banking machines, ATMs, cash handling devices, and the like.